UAMS' AI playbook for capacity lift & fewer cancellations

Manual, fragmented pre-admission testing strains perioperative teams and the operating room. Phone tag for histories, missing documents and late risk discovery all drive day-of-surgery delays, idle rooms and staff burnout. Leaders need a faster, more reliable way to prepare patients without adding FTEs.

 

University of Arkansas for Medical Sciences (UAMS) reworked its pre-admission testing model with AI-enabled workflows to give each nurse an assistant for information gathering, risk flagging and follow-up tasks. The result: a 50% increase in PAT nurse capacity, a 25% reduction in surgical cancellations and a 60% drop in manual document processing time.

In this webinar, you will learn how to:

  • Supercharge pre-admission testing programs with AI
  • Successfully implement an AI solution, ensuring staff adoption and integration into existing workflows
  • Use AI to enhance staff productivity and optimize patients before surgery
PRESENTERS

Meet the expert speakers

Tammy Jones

Tammy Jones

Chief Nursing Officer / Associate Vice Chancellor for Patient Care Services & Clinical Operations, UAMS

Alvin Stewart

Medical Director, Urology Center / Epic Anesthesia Operational Lead / Anesthesiologist, UAMS

Andrew Fisher

Co-Medical Director, Perioperative Care Coordination, Qventus

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